We’ve learned from the readings this week all of the vital
factors that must go into forecasting, and how forecast models are determined.
We also learned the uncertainty of forecasting and how to minimize that error.
What happens when reputable company overlooks a major factor and what is the
cost of forecast error?
In April of this year, the Walgreens CFO predicted $8.5
billion in pharmacy unit earnings for the end of 2016. He then lowered this
prediction by $1.1 billion in July. This error caused the CFO of Walgreens and
the president of the pharmacy, health and wellness division to step down. Walgreens
has recently made efforts to become a larger middleman in dispensing
prescription drugs under the Medicare Plan D plan. Medicare Plan D also plays a large role in
Walgreens’ supply chain as it receives 25- 30% of its prescription drugs from
this plan. Walgreens attributes this error to not accounting for the recent
increase in the cost of generic drugs that Walgreens sells. Walgreens also had a lower pharmacy margin
last quarter because of a pressure to reimburse third parties. Walgreens says
it plans to find way to lower expenses to offset the decline of gross margin
(50 basis points). This error also caused Walgreen’s stock to lower.
As we learned in the readings, all forecasts have a level of
uncertainty, but it is important to minimize that uncertainty or even measure
that level of uncertainty. It is also important to collect as much data as
possible to develop the metric that you wish to forecast. Data and vital
information should not be ignored while developing a forecast. Another vital
component of forecasting is to integrate suppliers into the process. In this
example, Walgreens left out vital information while forecasting its
pharmaceutical earnings. The cost of the generic drugs that Walgreens sells
should have been accounted for, as it is a major part of the supply chain. Why
hadn’t Walgreens considered the cost of its suppliers? When a company has a
forecasting error this large it misleads investors, causes reputational damage,
disrupts the supply chain process, and in this case, causes two executives
their jobs.
It is important to evaluate all factors in a supply chain
while undergoing the forecasting process. Leaving out one factor can have
serious consequences greater than a rounding error. This makes me question the
methods that companies use to develop their forecasts and how much they can be
trusted. Should we try to understand the process that they use of simply trust
the information that is put out?
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